Huoran Li
Huoran Li
Software Engineering Institute, Peking University, Beijing, China
Verified email at pku.edu.cn - Homepage
Title
Cited by
Cited by
Year
Characterizing smartphone usage patterns from millions of android users
H Li, X Lu, X Liu, T Xie, K Bian, FX Lin, Q Mei, F Feng
Proceedings of the 2015 Internet Measurement Conference, 459-472, 2015
1202015
Through a gender lens: learning usage patterns of emojis from large-scale Android users
Z Chen, X Lu, W Ai, H Li, Q Mei, X Liu
Proceedings of the 2018 World Wide Web Conference, 763-772, 2018
652018
PRADA: Prioritizing android devices for apps by mining large-scale usage data
X Lu, X Liu, H Li, T Xie, Q Mei, D Hao, G Huang, F Feng
2016 IEEE/ACM 38th International Conference on Software Engineering (ICSE), 3-13, 2016
462016
Understanding diverse usage patterns from large-scale appstore-service profiles
X Liu, H Li, X Lu, T Xie, Q Mei, F Feng, H Mei
IEEE Transactions on Software Engineering 44 (4), 384-411, 2017
442017
Voting with their feet: Inferring user preferences from app management activities
H Li, W Ai, X Liu, J Tang, G Huang, F Feng, Q Mei
Proceedings of the 25th International Conference on World Wide Web, 1351-1362, 2016
322016
Deriving user preferences of mobile apps from their management activities
X Liu, W Ai, H Li, J Tang, G Huang, F Feng, Q Mei
ACM Transactions on Information Systems (TOIS) 35 (4), 1-32, 2017
272017
Predicting smartphone battery life based on comprehensive and real-time usage data
H Li, X Liu, Q Mei
arXiv preprint arXiv:1801.04069, 2018
162018
Prado: Predicting app adoption by learning the correlation between developer-controllable properties and user behaviors
X Lu, Z Chen, X Liu, H Li, T Xie, Q Mei
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2017
162017
Security analytics for mobile apps: achievements and challenges
W Yang, X Xiao, D Li, H Li, H Wang, Y Guo, T Xie
Journal of Cyber Security 1 (2), 1-14, 2016
92016
A descriptive analysis of a large-scale collection of app management activities
H Li, X Liu, W Ai, Q Mei, F Feng
Proceedings of the 24th International Conference on World Wide Web, 61-62, 2015
82015
Mining device-specific apps usage patterns from large-scale android users
H Li, X Lu
arXiv preprint arXiv:1707.09252, 2017
72017
Systematic Analysis of Fine-Grained Mobility Prediction with On-Device Contextual Data
H Li, F Lin, X Lu, C Xu, G Huang, J Zhang, Q Mei, X Liu
IEEE Transactions on Mobile Computing, 2020
42020
Mining usage data from large-scale android users: challenges and opportunities
X Lu, X Liu, H Li, T Xie, Q Mei, D Hao, G Huang, F Feng
2016 IEEE/ACM International Conference on Mobile Software Engineering and …, 2016
12016
Method and system for determining quality of application based on user behaviors of application management
X Liu, G Huang, H Mei, H Li, X Lu
US Patent 10,997,637, 2021
2021
A Systematic Analysis of Fine-Grained Human Mobility Prediction with On-Device Contextual Data
H Li
arXiv preprint arXiv:1901.10167, 2019
2019
Method of selecting mobile device models for application development on basis of user operational profiles
X Liu, G Huang, H Mei, X Lu, H Li
US Patent App. 15/746,450, 2018
2018
Mining Device-Specific Apps Usage Patterns from Appstore Big Data
H Li, X Liu, H Mei, Q Mei
CCF Conference on Big Data, 55-76, 2018
2018
Mining Behavioral Patterns from Millions of Android Users
X Liu, H Li, X Lu, T Xie, Q Mei, H Mei, F Feng
arXiv preprint arXiv:1702.05060, 2017
2017
IEEE/ACM 38th IEEE
X Lu, X Liu, H Li, T Xie, Q Mei, D Hao, G Huang, F Feng
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